*A focus on normal theory linking average power, expected power, predictive power, assurance, conditional Bayesian power and Bayesian power. *Extensions of the concepts to binomial, and time-to-event outcomes and non-inferiority trials *An investigation into the upper bound on average power, assurance and Bayesian power based on the prior probability of a positive treatment effect *Application of assurance to a series of trials in a development program and an introduction of the assurance of an individual trial conditional on the positive outcome of an earlier trial in the program, or to the successful outcome of an interim analysis *Prior distribution of power and sample size *Extension of the basic approach to proof-of-concept trials with dual success criteria *Investigation of the connection between conditional and predictive power at an interim analysis and power and assurance *Introduction of the idea of surety in sample sizing of clinical trials based on the width of the confidence intervals for the treatment effect, and an unconditional version.